During the last 50 years, purely digital computer science of the Von Neumann type have made considerable progress. However, even the most powerful computers provided with the most developed algorithms do not manage to rapidly process problems which are apparently simple, such as the interpretation of an image, which is however achieved in a fraction of a second by the human brain.
The latter, actually operates in a massively parallel and analog way, unlike present computers. The brain typically consists of 1011 neurones interconnected together. A neurone is connected to another neurone through a synapse. Each neurone is connected to on average 10,000 other neurones. This very high density of interconnections is essential for ensuring a massively parallel processing of information and a self-learning function.
Many studies deal with the possibility of producing neuromimetic circuits, i.e. mimicking the operation of the human brain, in order to go beyond conventional architectures in order to allow cognitive processing of information.
These studies have been re-initiated since 2008 following the arrival of components called memristors. This is a component having an electric resistance which may be modified by applying a suitable stimulus and having the capability of retaining the value of the thereby modified resistance. A memristor is therefore a component having a changeable property in an analog way and having the capability of storing in memory this modification (non-volatile nature).
This change in resistance may be induced by a Redox reaction, a phase transition, a change in the properties of an organic layer, by a purely electronic effect (eg: spin, ferroelectric polarization, etc.).
From among memristors unidimensional nanometric objects are known such as for example nanowires and nanotubes with a phase transition. In particular, many studies have been developed in the field of the growth of nanowires based on GeSbTe, GeTe and InSe.
However, since the discovery of memristors, a limited number of studies have dealt with the architecture of circuits. These studies contemplate a «top-down» approach, according to which a circuit is designed, and then produced by micro- or nano-electronics methods, such as lithographic methods. For example this means making a network of conductive wires, each wire being connected to input and output terminals. Two networks are then superposed at right angles and the wires of a network are interconnected to wires of the other network through a memristor.
The thereby obtained circuits are complicated. However, the interconnection density remains limited by the spatial resolution of the methods used. The fabrication methods are difficult to apply. The achieved circuits are therefore expensive.